DISTRIBUTION STRATEGIES AND PERFORMANCE

OF KENYA MEDICAL SUPPLIES AUTHORITY

KANYANGI FREDRICK OPATI

D61/67002/2011

A Research Project Submitted in Partial Fulfilment of the

Requirements for the Award of Degree of Master of Business

Administration, School of Business. University of Nairobi

2018

ii

DECLARATION

I declare that this Research Project is my original work and has never been submitted

to any other university for assessment or award of a degree.

Signature …………………………………………… Date …………………………...

KANYANGI FREDRICK OPATI

D61/67002/2011

This Research Project has been submitted with my authority as the University

Supervisor.

Signature …………………………………………… Date ……………………………

SUPERVISOR:

MR. ONSERIO NYAMWANGE

Department of Management Science, School of Business, University of Nairobi

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ACKNOWLEDGEMENTS

A very special appreciation to my supervisor, Mr. Onserio Nyamwange for his guidance

and great support during the undertaking of this project. I also express my gratitude to

other members of the department of Management Sciences and the MBA coordinating

office. To my family particularly my wife Glorian Agesa for the support during the

entire period was enormous. Lastly, KEMSA staff for the provision of information

required for this project.

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DEDICATION

I dedicate this work to my brother Johnstone Nyarigu for his encouragement to keep

going and support during the entire duration.

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ABSTRACT

This study sought to investigate the extent to which strategies adopted by Kenya

Medical Supplies Authority (KEMSA) seem to be ineffective as health facilities do not

receive the Medical Supplies on time and the orders received do not match the

demanded quantities. The specific objectives were to identify the medical distribution

strategies adopted by KEMSA; and to determine the impact of the distribution strategies

adopted on the performance of KEMSA. The study employed descriptive case study

design. Data was collected by use questionnaires and analysed quantitatively and

qualitatively. The study established that KEMSA adopted three strategies that included

pull strategy, push strategy and a mixed strategy comprising of both push and pull

elements. The study also established general improvement in application of pull

strategy. The study established that push strategy was applied in 2011 and 2012 and not

applied thereafter. On mixed strategy comprising of some push and pull elements, the

study established that there was fluctuation in the trends between 2011 and 2015. The

study found that there was improvement in performance of the institution from 2011 to

2015. On impact of the strategies on performance, the study established that that there

was strong correlation between both pull and push strategies and performance. The

findings, however, indicated weak correlation between pull strategy and performance

as well as push strategy and performance. The study also established that all strategies

employed are important factors influencing KEMSA performance but at varying

degrees where mixed strategy of both push and pull contributed most to the

performance followed by pull strategy then push strategy. In view of the findings, the

study concluded that while KEMSA has adopted three distribution strategies, the pull

strategy is most applied and push remained relevant despite not being applied. The

study also concludes that while pull strategy is most applied, the performance of

KEMSA is largely affected by application of combination of both push and pull

strategies. However, while the performance of KEMSA is largely determined by

combination of both push and pull strategies, it remains fair and there is opportunity for

improvement in the distribution of pharmaceuticals and equipment. It is with these

findings that the study recommended re-application of push strategy. The study also

recommended for KEMSA to address the challenges that reduce efficiency and

effectiveness in each of the strategy applied.

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TABLE OF CONTENTS

DECLARATION ........................................................................................................... ii

ACKNOWLEDGEMENTS ......................................................................................... iii

DEDICATION .............................................................................................................. iv

ABSTRACT ................................................................................................................... v

LIST OF TABLES ..................................................................................................... viii

LIST OF ABBREVIATIONS ....................................................................................... ix

CHAPTER ONE: INTRODUCTION ....................................................................... - 1 -

1.1 Background of the Study .................................................................................... - 1 -

1.2 Research Problem ............................................................................................... - 7 -

1.3 Research Objectives ............................................................................................ - 8 -

1.4 Value of the Study .............................................................................................. - 8 -

CHAPTER TWO: LITERATURE REVIEW ......................................................... - 10 -

2.1 Introduction ....................................................................................................... - 10 -

2.2 Theoretical Foundation ..................................................................................... - 10 -

2.3 Distribution Strategies ...................................................................................... - 12 -

2.4 Performance Measurement ............................................................................... - 14 -

2.5 Distribution Strategy and Organizational Performance .................................... - 15 -

2.6 Summary of Literature Review ......................................................................... - 17 -

2.7 Conceptual Framework ..................................................................................... - 19 -

CHAPTER THREE: RESEARCH METHODOLOGY ......................................... - 20 -

3.1 Introduction ....................................................................................................... - 20 -

3.2 Research Design................................................................................................ - 20 -

3.3 Study Population ............................................................................................... - 20 -

3.4 Data Collection ................................................................................................. - 21 -

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3.5 Data Analysis .................................................................................................... - 22 -

CHAPTER FOUR: DATA ANALYSIS, RESULTS AND DISCUSSION ........... - 23 -

4.1 Introduction ....................................................................................................... - 23 -

4.2 Distribution Strategy Adopted by KEMSA ...................................................... - 23 -

4.3. Performance of KEMSA in Supply of Medical Items ..................................... - 34 -

4.4 Impact of the Distribution Strategies on the Performance of KEMSA ............ - 35 -

CHAPTER FIVE: SUMMARY, CONCLUSION AND RECOMMENDATIONS- 39 -

5.1 Introduction ....................................................................................................... - 39 -

5.2 Summary of Findings ........................................................................................ - 39 -

5.3 Conclusions ....................................................................................................... - 41 -

5.4 Recommendations ............................................................................................. - 41 -

5.5 Limitations of the Study.................................................................................... - 41 -

5.6 Suggestions for further Studies ......................................................................... - 42 -

REFERENCES ....................................................................................................... - 43 -

APPENDICES ........................................................................................................ - 48 -

Appendix 1- Introduction Letter ............................................................................. - 48 -

................................................................................................................................. - 48 -

Appendix 2- Questionnaire ..................................................................................... - 49 -

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LIST OF TABLES

Table 4.2: Distribution Strategy Adopted by KEMSA between 2011 and 2015 .... - 23 -

Table 4.3: Trends of Pull Strategy .......................................................................... - 25 -

Table 4.4: Trends of Push Strategy ......................................................................... - 30 -

Table 4.5: Trends of Both Pull and Push Strategy .................................................. - 33 -

Table 4.6: Performance of KEMSA ........................................................................ - 34 -

Table 4.7: Correlations between Variables ............................................................. - 36 -

Table 4.8: Model Summary .................................................................................... - 36 -

Table 4.9: Regression Results ................................................................................. - 37 -

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LIST OF ABBREVIATIONS

BRP Business Process Re-Engineering

CSC Collaborative Supply Chain

GOK Government of Kenya

KEMSA Kenya Medical Supplies Authority

MOH Ministry of Health

MSH Management Sciences for Health

SC Supply Chain

SCM Supply Chain Management

TQM Total Quality Management

USA United States of America

USAID United States Agency for International Development

WHO World Health Organization

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CHAPTER ONE: INTRODUCTION

1.1 Background of the Study

Distribution is very crucial in the process of supply chain management particularly of

medical products (pharmaceuticals and equipment). different entities and individuals

are fully responsible for the process of handling, distribution and storage of products.

However, in other incidences, a person is only entitled to take control of certain

distribution elements especially medical supplies (WHO, 2010). The World Health

Organization considers entrance to medicine as one of the priorities for the citizen,

where supply chain in medicine is very necessary (WHO, 2003). In Kenya, medical

supply is mainly a function of KEMSA, a corporation that falls under the ministry of

health (KEMSA act, 2013) .

Kenya Medical Supplies Authority, has for the past period received bad publicity and

reputation and is known for inconsistent customer service and inefficiencies in its

operation. In July 2007, KEMSA’s performance started declining and in June 2008, its

operations had come to a near halt (GOK, 2008). The Authority has been under a series

of transformation and yet the bureaucracies have been its biggest impediment.

KEMSA’s medical supply chain has suffered from great short-term demand

fluctuations with serious adverse effects to the Kenyans (GOK, 2008).

An efficient and effective type of supply chain management is characterised by high

level of reliability, timeliness, easy movement of health products as well as data up and

down the supply chain module: from the point of service delivery (this include clinics,

hospital and health posts where the health commodities are well dispensed) to national,

county as well as sub county levels. Data from this point of service are very important

and relevant for supply chain managers for decision making. This kind of decisions

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include the type of health commodities that are supposed to be delivered and at what

time. The paper-based type of logistic management system is commonly applied in third

world countries; the right person does not commonly access right data at the right time.

(Frost, Islam, Printz, Whitehouse, & Hiller, 2011). This points to inefficiencies in the

supply chain which has adverse impact on the health sector. There is need for

eliminating such inefficiencies especially in the wake of improving Universal Health

Coverage.

1.1.1 Distribution Strategy

Distribution Strategy is a plan to make a product or a service available to the targeted

customers through its supply chain. The supply chain is lowest of the business network.

It is defined as the human capital management, processing of business, information as

well as material between the business, its customers as well as its suppliers. This allows

for maximum customer satisfaction with maximum business margin (McNeil,

2007). What is important is to be put into consideration all supply chain participants

that can acquire benefit from improved functions of supply chain management

Distribution is very crucial in the process of integration of supply of equipment as well

as medical drugs. Different people and organisations are responsible for sourcing of

product, procurement, transporting them, delivery of these products, storage, tracking

devices, installing, commissioning, maintenance as well as service. This ensures safety

as well as performance of those medical equipment at the point of (Medical Device

Authority, 2013).

The “push” strategies maximise use of firm sale force as well as trade promotions to

enable creation of demand from consumers for the products. In this particular scenario,

producers are able to promote the products to the wholesalers make use of the firm’s

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trade promotion and sales force to come up with the consumer demand for the company

products. In this type of strategy, wholesaler’s products are promoted from the

producer, then wholesalers promote their products to the retailers and finally patient’s

drugs are promoted by the retailers. Practically, the company is able to promote its

product to the pre-wholesalers, then wholesalers or the pharmacy or give focus to one

of the channels. In the type of pull strategy, the consumers themselves request the

products and eventually pulls them all through the distribution channel. Information is

very important in the process of offering effective channels of distribution. Moreover,

finance is the major engine that enhance all this. In most of the countries, the public

health officials have very limited experience in the process of designing the procumbent

system that is very optimal. This includes the system of distribution that can perfectly

fit the current market (Oyamo & Mburu, 2014).

Most countries are radically moving away from the pharmaceutical system of

procurement whose operation are done by the public sector and investigations are

underway to involve the public sector too in order to strengthen public health. The

publication of MSH/WHO (2007) shows the existence of the various modes (Oyamo &

Mburu, 2014). In Kenya, KEMSA has the mandate of medical supplies and this has

limited participation of the private sector. Until the mandate is revised, KEMSA will

therefore continue as major supplier of medical supplies to public and private medical

entities. This implies that any inefficiencies cannot currently be addressed by adopting

integrated procurement system that allows private sector to procure and supply medical

supplies. Therefore, there is need to identify and address inefficiencies in KEMSA’s

distribution strategy as a means of improving KEMSA’s performance.

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1.1.2 Firm Performance

A firm’s key dimensions of lean supply chain’s performance is well defined in terms

of the speed of delivery, level of reliability of delivery, flexibility and price of the drugs.

Time is one of the fundamental measures as well as competitive advantage for the

performance of lean supply chain. Many companies maximize use of the balanced

scorecard developed by Kaplan & Norton’s (1992). The model is mainly based on the

principle that states that, an efficient system of performance be in a position to provide

managers with the effective information to address these questions: how do we look at

our shareholders in the financial perspective? How can our customers be in a position

to see the company? This is called customer perspective. Finally, how can we be in a

position to improve and create the value? This is called learning and innovation

perspective. The model helps the company to translate its strategy as well as vision

through the objectives and measures defined apart from stressing on the need for the

financial measures that provide minimal (Onyango, 2013).

The model of supply chain performance refers to the extended activities of supply chain

in the process of meeting the requirements of the end customers that includes the

availability of the products, timely product delivery as well as all necessary inventory

as well as capacity in the process of delivering the service in the manner that is very

effective (Harrison et al.,2005). The measure of performance is quantitatively able to

elaborate something that is very crucial concerning our product as well as service and

their production process. The measure of performance let every person to know: how

best we are faring on, whether we are meeting the company goals, whether the

customers are satisfied or not, if the whole process is controlled statistically and where

improvements can be done (Onyango, 2013).

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Distribution decisions in most cases are based on long-term forecasts. An adequate

forecasting system is often necessary to structure any distribution system. Distribution

system may be as a response of the business in the process of anticipation of the demand

of customers. From the whole viewpoint of supply chain, deciding whether this type of

supply chain is a pull or a push is very difficult and depend on what constitute the

supply chain process and where specific participants are placed in the supply chain

model (McNeil, 2007).

Public Health Programs require supply chain to ensure that the product is available and

when it is needed. Implementation of the indicators of supply chain indicators or the

metrics as one of the simplest and least expensive and less time-consuming activity in

the operations improvement. It is very crucial for the metrics to be able to align and not

work to counter the process (Aronovich, 2010). This study therefore examined the

extent to which distribution strategy are suitable or not.

1.1.3 Kenya Medical Supplies Authority

Kenya Medical Supplies Authority (KEMSA) is the corporation of the state established

under the ministry of health that as established under KEMSA act of 2013 whose

function is to procure, store and distribute medical supplies for public program

prescription. KEMSA is also mandated to establish the storage network, packaging as

well as packaging and provision of distribution facilities for provision of the drugs as

well as medical supplies in the different health institutions. KEMSA has been mandated

to enter into the partnership in an established framework with the county governments

for the reason of providing procurement services, storage and distribution of the drugs

as well as supply of drugs.

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Since 1901, the institution has undergone transformation aimed at improving service

delivery. The authority has gone a long way in the process of addressing the historical

challenges through the system of supply chain. The company corporate mission hinges

on the ability to optimise on use of efficient procurement system as well as distribution

and storage of the value for money drugs to the facilities of the public (KEMSA, 2014).

Part of the transformation aimed at improving efficiency in its supply system is the

adoption of the pull and push system that has greatly depended on the characteristics of

the medical products they handle. The supply chain with higher demand uncertainties

and have higher unit cost including low transportation cost relative to the product’s total

cost then this can have a better fit for the pull system or commonly known as the

demand driven system. On the other hand, products that have low demand uncertainties

and require high economy of scale would preferably have greater cost saving from

pooling and pushing the distribution (Kamau, 2006).

It is against the backdrop in service delivery that on 10th July 2008, KEMSA Board

was dissolved and Task Force formed following concerns over KEMSA’s declining

performance. The Task Force was mandated to make legislative and policy

recommendations that would empower KEMSA to discharge its mandate. In carrying

out its work, the Task Force examined numerous documents and interviewed several

people whom it considered to be representative of all the stakeholders of KEMSA,

including government officials, health facilities staff, development partners, suppliers,

transporters, KEMSA staff, members of the dissolved board of directors and the

suspended chief executive (GOK, 2008). From these unprecedented events, there is

need to examine the factors that have hindered the achievement and the full

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implementation of an appropriate distribution strategy by the Kenya Medical Supplies

Authority.

1.2 Research Problem

Distribution of the equipment as well as the pharmaceutical drugs is very important of

effective management of the drugs and supply which is very important in all institutions

of healthcare (WHO, 2007). A framework and institution to support effective

distribution system is therefore necessary. The framework and institution should

therefore be responsive to emerging needs in the medical field. In Kenya, KEMSA as

an institution operates the framework of medical supplies. The institution has

undergone transformation aimed at improving efficiency in the distribution system.

However, the transformation of KEMSA to meet local and international standards in

service delivery of medical supplies has not been achieved. The adoption of push and

pull strategies as part of the transformation strategies is not meeting the expectations of

the procurement requirements of medical supplies recommended by the World Health

Organization (WHO). The WHO recommends for the efficient supplies of medical

equipment through the concept of just-in-time that requires timely supply in respect to

demand (Taskforce, 2008). At KEMSA, the strategies adopted seem to be ineffective

as health facilities do not receive the medical supplies on time and the orders received

do not match the demanded quantities. This unprecedented reality compromises

medical services in the medical facilities which puts many lives at risk.

The emerging questions in this situation therefore revolve around the type or system or

strategy of distribution adopted by KEMSA and effects on KEMSA’s performance in

distribution of medical supplies. It is against the backdrop of the inefficiencies in the

distribution of drugs and other medical supplies that this study sought to investigate the

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distribution strategies adopted at the Kenyan Medical Supplies Authority and the

impact they have on the performance of the Authority. The study is seeking to answer

the questions: what are the distribution strategies adopted by KEMSA in the distribution

of medical supplies? What impact do the distribution strategies adopted have on the

performance of KEMSA?

1.3 Research Objectives

This study was guided by the following objectives:

1. To identify the medical distribution strategies adopted by KEMSA.

2. To determine the impact of the distribution strategies adopted on the

performance of KEMSA.

1.4 Value of the Study

It is anticipated that this study would be important in several ways to KEMSA, Health

Sector stakeholders and researchers. The management of the Kenya Medical Supplies

Authority (KEMSA) will have important information to enable them to improve in their

core functions. Best distribution strategy would be developed to address the challenges

resulting into stock outs of drugs in most of the health facilities in the County which

have a cumulative effect ranging from deaths and complications of other simple

illnesses.

The health sector has several partners including donors, civil societies, and the public

and this research will provide information for policy making and would go further in

encouraging them continue in their efforts of funding the sector. In addition, the

Ministry of Health will find it easy in their planning and allocation of available

resources as well as County governments improving on provision of health services.

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Finally, this study finding would enhance other researchers to try and establish other

issues that would not have been satisfactorily established and thus form a basis of future

research

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CHAPTER TWO: LITERATURE REVIEW

2.1 Introduction

This section describes reviewed different literature relation to the KEMSA’s functions

and findings from the perspective of other researchers. The chapter is outlined under

the following subheadings: theoretical foundation; medical distribution strategy;

Performance measurement; distribution strategy and performance of KEMSA; and

conceptual framework.

2.2 Theoretical Foundation

This study adopted Michael Porter’s Competitive Advantage of Nation’s theory which

provides a tool for analysing competitiveness with all its implications focusing upon

individual industries, or clusters of industries, in which the principles of competitive

advantage are applied (Porter, 1990). Hitt, Ireland, and Hoskinsson (2015) says that a

competitive strategy that is winning is always established on the market that is

predictable, consistent and understanding. The main objective of this strategy of

business is to be able to accomplish the competitive advantage that is very sustainable.

A competitive advantage arises when the company is in position to deliver the same

benefit just like a competitor but at slightly lower cost or be in a position to deliver the

benefits that are above that of the competing firms. Currently, the existence of

technology that is dynamic calls into question the level of sustainability of the

competitive advantage. Managers have been able to embrace Total Quality

Management, product reengineering and benchmarking as the tool to improve on

product quality, improvement of production of the products as wells as the production

speed (Safford, 2005).

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Any company can have or acquire the competitive advantage whenever it acquires a

competitive edge over its rival in acquiring customers and being in a position to defend

the company against the prevailing competitive forces (Thompson & Strickland, 2002).

The sustainable competitive advantage emanates from the core competencies that

improves the company benefits. To be in a position to succeed in building a reliable

competitive advantage a company must be able to produce what the firm will perceive

to be of stronger value. This means the company should produce and sell products at a

lower price, or products of better quality that customers can pay more for them without

complaining. It consists of all kind of moves as well as approaches that a company has

is taking in order to attract more customers without pressure hence improving its

competition in the market (Thompson & Strickland, 2002). It is concerned with what

the company is able to do in order to gain its competitive advantage

Porter (1990) provides an outline three major approaches to achievement of competitive

strategy with the aim of being a low-cost producer. This is also called low cost

leadership strategy, seeks to achieve product differentiation from the other companies

this is called differentiation strategy and finally narrow portion of the market focus, this

is also called niche or focus strategy. Many drug firms are highly interested with

acquiring profit from efficient product movement from the producers to the patients.

The payers are interested in the right channel that can be in position to offer these types

of products at as lowest price as possible without necessarily aligning to the interest

(McCain, 2012).

To hold down distribution costs KEMSA’s customer base places their replenishment

orders on a quarterly basis. While this helps to minimize the distribution costs, it may

not fully account for the additional inventory costs required for the facilities to maintain

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their inventory. With only four opportunities to order each year, the average inventory

for a facility will be three times as large compared to the opportunity to order 12 times

per year. For example, if a facility had an annual consumption rate on a commodity for

100,000 units, they would need to order on average 25,000 units each quarter. If they

were able to order monthly, their average order would fall to 8,333 units per order. In

addition, with the variability in demand, there is a greater probability of facility out-of-

stocks when ordering only four times per year as well as a longer duration between

replenishments (Nzioka, 2010).

2.3 Distribution Strategies

A push-based chain of supply aligns their distribution and production decision making

process towards long term forecast. Most of the manufacturers makes the forecast of

their demand by basing on their previous orders received from their distribution centers

and retailers’ warehouses. A preplanned schedule of manufacturing is conducted and

then their products are pushed down to the supply chain the inventories of the vendors

irrespective of the information demand patterns available at that time. The demerits of

this kind of push is that; the company may be unable to meet the prevailing market

demand; there may be a very high likelihood of obsolescence in the supply of inventory

as the demand of the specific type of products vanishes (Wang' & Wittwer, 2007).

The bullwhip effect mostly take place in the push system. Backward along the chain of

supply, many suppliers tend to place larger type of orders up to the downstream demand

of uncertainty in order to meet the demand of the customers hence making the entire

system to be unstable. In such kind of system, the level of service is very low as the

system is not able to respond to the requirement of the service. This makes the products

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to be obsolete. The pull-based supply system the decision on the production and

distribution is based on the demand of the customers (Wang' & Wittwer, 2007).

In ideal pull system, orders come before the inventories are held. This is made a success

by fast flow of the information concerning the demand of the customers to different

supply chain participants. This type of system has many advantages. This includes;

stable system of supply chain and low inventory level. No perfect pull or push system

of supply chain exists hence most of the systems operates in combination of both

(Kaminsky & Simchi-Levi, 2003). High uncertainty of demand encourages very high

level of the pull strategy while the high economic conditions gives room for incentives

to high degree of the push system(Wang' & Wittwer, 2007).

The plan also foresees KEMSA to implement the central system of procurement that

are handled by Ministry of Health and simultaneously improve the supply chain logistic

capacity. The plan requires the government to engage in continuous capacity building

for this enhanced role for KEMSA. In fact, one of the planned key outputs for

commodity supplies management is to strengthen the capacity for the management of

the drugs as well as the management of drugs using latest information system (Kamau,

2006).

In the United States of America, Hospitals are now applying lean principles to their

inventory systems to improve efficiency and reduce operating costs. In this case, there

has been a medical dispensing technology to improve their pharmaceutical inventory

system. A recent study conducted by the Supply Chain Resources Cooperative suggests

that hospitals engaging in those new medical dispensing technologies will over an

estimated period of five years realize a significant benefit that will contribute to meeting

the required mandate (Handfield, 2007).

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According to Handsfield (2007), if the United States of America companies for example

learnt over a period of ten years that effective managing inventory is central to

remaining competitive. Although in practice maintenance of high inventory level is

acceptable, it in most cases resulting into high cost of carrying, diminished market share

and profit reduction among others. According to Shook (2010), “Lean Supply Chain is

a philosophy that seeks to shorten the time between customers’ order and the shipment

to the customer by eliminating waste”. However, the details provided on the benefits of

pull strategy in supply chain management, not many participants can apply the demand-

pull model. The organization that apply this type of model will always strive to move

the inventories from the point of decoupling to its supplier or suppliers’ supplier

(Shook, 2010).

2.4 Performance Measurement

The high need to come up with the latest system of performance measurement system

at different levels of the decision making resulted to Robert S. Kaplan and David P.

Norton (1992) to be able to develop and propose the balanced scorecard to help in

evaluation of the corporate performance from four different dimensions: learning and

growth, customers, financial perspectives and internal processes. Contrary, under the

latest market trend in terms of the environment (Green supply chain), leanness (Lean

supply chain) collaborative method (CSC type of collaborative method),

communication technology among others results to contemporary oriented perspective

as well as future of supply chain in the era of dynamic technology (Jaimes, Serna, &

Buritica, 2012).

Organizational management needs measurement of development of performance

system adopted by group of companies which is considered as one of tool for impacting

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more on the supply chain management (Ballou et al, 2000; Lancioni, 2000). Most of

the performance management system maximize use of modern approaches like

Balanced scorecard, TQM, business process reengineering or benchmarking. The

performance measurement is considered as part of the overall system of management

hence it is viewed as one of the system of quantifying the effectiveness of the actions

taken. It is one of the most common practice in the public performance measurement

of the public sector. It talks about three Es of; Effectiveness, Economy and Efficiency

(Consultant, 2003)

2.5 Distribution Strategy and Organizational Performance

The rapid distribution of the medical supplies performs a very important function in the

assurance of the efficiency as well as effectiveness of the healthcare system. The

medical distribution and supply entails movement of the large volume of diverse

products that are supposed to be delivered rapidly (Maged, Fernando, Honzhong,

Zhihong, & Daniel, 2009). The network of drug distribution for example have been in

the chaotic state as it consists of the open market, community pharmacies that are

managed by the Non-Governmental organisations, medicine stores, public and private

hospitals, importers as well as pharmaceutical manufacturers resulting into ineffective

process of procurement as well as channels of distribution (Oyamo & Mburu, 2014).

According to Kahia and Iravo (2014) in their study of Bata Shoe Company limited, it

was found out that product, customers, technology as well as the structure of

distribution are among the factors that affect the logistics of distribution. The research

work also determined the quantities ordered, location of the customers, the

requirements of the customers and the customer numbers as among the aspects that

affects the performance of the logistics of distribution

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In his study, Kadivane (2012) sought to find out supply chain management strategy and

performance of KEMSA. In the study recommendations, he asserts that there is need

for an investigation and focus on the innovation and developing of the overall

distribution strategy (for example investigate the applicability of new technologies and

resources in SCM) that would enhance KEMSA’s competitive advantage.

Over the ten years of KEMSA’s existence, the organization has implemented a

centralized supply chain network, established scheduled deliveries to all of its five

thousand plus customers through outsourced transport and continues to serve its

customers. However, its distribution functions remain plagued by operational

inefficiencies according to reports by the Ministries of Health (MOH), the United States

Agency for International Development (USAID) and the World Bank.

As at July 2008, KEMSA had a total distribution network that consisted of a total of

eleven network of warehouses that was well spread across 9 towns with a total storage

space of 292, 810 square feet. The previous assignment established that do not meet the

international good distribution practices as recommended by the World Health

Organization (Nzioka, 2010). This research therefore aims at investigating the

contribution of the strategy in the performance of KEMSA related to its mandate.

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2.6 Summary of Literature Review

Table 2.1 Summary of Literature Review

Author Research Findings Research Gap(s)

Maged Dessouky,

Fernando Ordenez,

Horgzhong Jia and

Zhihong Shen, 2009

Rapid Distribution of

Medical Supplies

Some important issues in the design of an efficient

pharmaceutical supply chain involve deciding

where to place the warehouses/

inventories and how to route distribution vehicles.

Solving appropriate facility location and vehicle

routing problems can ensure the design of a logistic

network capable of rapid distribution of medical

supplies. Both these problems must be solved in

coordination to quickly disburse medical supplies

in response to a large-scale emergency.

This research focused on rapid

distribution of medical supplies

in Los Angeles, USA and was

regarding an approach

hypothetical to an anthrax

emergency in that region.

George Mutua Nzioka,

2010

The Practice of Supply

Chain Management in

Public Healthcare Sector

in Kenya: The Case of

Kenya Medical Supplies

Agency

Although the KEMSA taskforce report of 2008,

highlighted financial and managerial problems at

the core of KEMSA’s inefficiencies, it is apparent

from this report that its SCM processes were not at

par with industry best strategy.

The study highlighted several areas where

KEMSA’s SCM processes can be improved to be

at par with industry best strategy.

This study focused on the SCM

processes at KEMSA and

attempted to link these

processes to the reported

performance by the taskforce

report of 2008. This study

concluded that the

unfavourable performance

could have been due to

managerial and financial

shortcomings as reported in the

taskforce report of 2008 as well

as the findings of this report.

- 18 -

Author Research Findings Research Gap(s)

(Kanavos, Schurer, &

Vogler, 2011)

The pharmaceutical

distribution chain in

The European Union:

structure as well as

impact on the prices of

pharmacies.

In the European Union, Manufacturers recognize

the importance and contribution of the distribution

sector to ensuring easy access as well as

availability of the drugs to the patients. It is

commonly argued that the distribution cost in many

occasions is not proportional to the offered value to

the public. This should be put into consideration

and be aligned to the contribution made by the

pharmaceutical sector in bringing unique

therapeutically alternatives into the market.

The study focused on the

distribution and access of

medicine to patients in the

European Union and the effects

on the pharmaceutical prices

with little attention on the

effect on the performance.

Samuel Kadivane Kazi,

2012

Supply Chain

Management Strategy

and Performance at

Kenya Medical Supplies

Authority

Innovative supply design has a very great effect in

the selection as well as corporation with the

suppliers. This improves the efficiency in the

supply chain hence this enhances supply chain

management strategy leading to improvement of

the performance

The researcher focused on the

general supply chain

management strategy and

challenges at KEMSA with no

attention on the distribution

strategy

Evelyne Akinyi Oyamo

and Daniel Kiarie Mburu,

2014

Effects of the process of

procurement process on

the distribution of the

Pharmaceutical Drugs in

the public hospitals in

the Kenyan country: A

case of the Mission for

Essential Drugs and

Supplies

The study established that specification design,

procurement planning, contracting and selection of

the supplier’s impact on the distribution of the

pharmaceutical drugs in the public hospitals

extensively in the MEDS.

The research further suggested that since the

research work is constrained to the Mission for the

Essential Drugs and Supplies, other research work

should be done in other organisations while

specialising on the supply as well as distribution of

the pharmaceutical drugs.

The research work was mainly

limited to the Mission for

Essential Drugs and Supplies

and how the design of

specification. Planning,

selection of suppliers and

specification of design impact

on the distribution of the

pharmaceutical drugs in the

public hospitals.

- 19 -

2.7 Conceptual Framework

The following conceptual model was developed as illustrated in Figure 2.1

Independent Variables Dependant variable

Source: Researcher, 2016

Figure 1 depicts the conceptual framework of the research. The model indicates

distribution strategies adopted and the impact on performance of KEMSA.

Push Distribution Strategy

Pull Distribution Strategy

Organisational Performance

- Effectiveness

- Efficiency

Figure 1: Conceptual Framework

- 20 -

CHAPTER THREE: RESEARCH METHODOLOGY

3.1 Introduction

This section covers the research design to be adopted in this study, the expected

respondents, collection of data and further how the data collected will be analysed.

3.2 Research Design

The research made use of a descriptive case study design. The study involved an

analysis of the distribution strategy at KEMSA. This design facilitated examination of

the supply strategies in terms of efficiency and effectiveness. Since the study involved

collection of data over long periods of time, mostly above five years it was helpful in

determining trend of the variables under study. It was possible to learn more about cause

and effect relationships among variables of the study. More data over longer periods of

time allowed for better understanding of the impact created by the strategies of

distribution at KEMSA. The study was limited to collecting data in the year 2015, 2014,

2013, 2012 and 2011.

3.3 Study Population

The study targeted KEMSA employees. KEMSA has 42 warehousing employees, 46

distribution and 21 procurement employees. The study targeted KEMSA employees

engaged in the receipt and dispatch of drugs and medical equipment. To arrive at the

suitable sample size of 28 respondents, Kothari’s (2004) sample size formula illustrated

in Table 1 was used.

𝑛 =Z2pqN

e2(N − 1) + Z2pq

Where: n: is the sample size for a finite population; N: size of population i.e. 109; p:

population reliability (or frequency estimated for a sample of size n), where p is 0.3

- 21 -

(30%) and p + q= 1; e: margin of error considered is 10% for this study; Z is the normal

reduced variable at 0.05 level of significance z is 1.96.

Table 3.1: Sample Frame

Respondents Category Population Sample

KEMSA employees Warehousing 42 10

Distribution 46 12

Procurement 21 6

Total 109 28

Source: Researcher, 2016

3.4 Data Collection

The study will target KEMSA employees particularly those engaged in the receipt and

dispatch of drugs and medical equipment. Structured questionnaires were used to

collect primary data. These questionnaires were designed to capture information on the

ordering, deliveries and the time taken to deliver an order to KEMSA, time taken to

receive drugs and equipment after processing from KEMSA including feedback where

required.

The questionnaires also contained sections with the likely impacts of their distribution

strategy adopted by KEMSA on its performance. A distribution summary form was also

used to collect additional information on the distribution practices for the years 2015,

2014, 2013, 2012 and 2011. This established the trend in performance for this period.

- 22 -

3.5 Data Analysis

The data was collected by use of questionnaires which was analysed quantitatively and

qualitatively. Quantitative analysis involved analysis of numeric data while qualitative

involved analysis of non-numeri data. The data was analysed quantitatively by use of

SPSS. The content analysis was supplied by use of the quantitative data. The findings

of the quantitative data outcomes were then presented using the statistical tables while

the quantitative finding was presented in form of themes.

Table 3.2 Summary of Data Analysis Methods

Objective Section of the questionnaire Data Analysis Method

To identify distribution

strategy adopted by

KEMSA.

Questionnaire Sections 1

Factor analysis

To determine the impact of

distribution strategy on

performance of KEMSA.

Questionnaire Section 2-12 Descriptive and

Inferential Analysis

- 23 -

CHAPTER FOUR: DATA ANALYSIS, RESULTS AND

DISCUSSION

4.1 Introduction

This particular section gives an analysis of collected from the KEMSA staff engaged in

the acquisition, receipt and dispatch of the medical drugs and equipment who were the

respondents. The chapter covers the efficiency of the strategies adopted by KEMSA;

the effectiveness of the strategies and the effect of the strategies on KEMSA

performance.

4.1.1 Questionnaire Response Rate

The questionnaire response rate was 86% which was considered suitable for data

analysis.

4.2 Distribution Strategy Adopted by KEMSA

Responses from the questionnaire were used to identify the distribution strategy

adopted by KEMSA. The findings are illustrated in Table 4.2.

Table 4.1: Distribution Strategies adopted by KEMSA between 2011 and 2015

Distribution Strategy Period Mean

2011 2012 2013 2014 2015

Push Strategy 10% 7% 6% 4% 3% 6%

Pull Strategy 38% 42% 52% 74% 83% 58%

Both pull and push strategies 52% 51% 42% 22% 14% 36%

The study under this section is meant to determine the distribution strategies adopted

by KEMSA. The findings in Table 4.2 indicate that KEMSA adopted two major

distribution strategies, the push strategy and pull strategy. The findings also indicate

- 24 -

that both strategies were also applied together. The findings in the Table also reveal

that pull strategy was most preferred (mean of 58%) while application of push strategy

reduced (mean of 6%) in the period between 2011 and 2015. The increasing application

of pull strategy from 2011 is attributed to effects of devolution where health sector was

mainly managed by County governments that maintained control over procurement of

medical supplies. This was also attributed to the supply chain improvement

recommendations by the Government’s Task Force Report (GOK, 2008).

The variation in the application of the strategies was based on various reasons. The

preference of pull strategy was demand driven since health facilities had different

consumption rates of their medical supplies and this allowed KEMSA to receive orders

of the supplies. This limited the application of push strategy. However, push strategy

remains relevant in cases of emergencies such as disease outbreaks where KEMSA was

compelled to supply some medical supplies as means of managing such emergencies.

The use of both push and pull strategies was relevant in cases where either push or pull

was unpredictable. Kaminsky & Simchi-levi, (2003) also noted practically, no perfect

pull as well as push system exists. The supply chain management is operated in both

combinations.

It was revealed that the guiding aspects for push strategy included situations of

projected demand findings which are similar to the study (Oyamo & Mburu, 2014).

Push strategy was also applied when consumption patterns of health facilities were

predictable. The prediction was obtained from health facility reports that supported an

established trend of consumption. In contrast, the preference of pull strategy over push

was attributed to several reasons. The first reason is that pull strategy reduced expiries.

Also, pull strategy ensured that specific requests were processed. This therefore reduced

- 25 -

the risk of supplying medical items that were not needed. In addition, pull strategy

supported proper preparation or planning to support the supply chain. In this case,

orders were processed and dispatched on rolling basis.

The findings on distribution strategy indicate that pull strategy was suitable as it

allowed stakeholder participation and it was easier to administer. These findings imply

that KEMSA has been operating an integrated distribution strategy that allowed for

flexibility in addressing varying needs at a given time. In this situation, while the

strategies are not equal, there are corresponding impacts of each strategy on KEMSA

performance of KEMSA in supply of medical items to different users.

4.3 Trends of Distribution Strategies and Performance of KEMSA

The trends of distribution strategies were analysed and presented in Tables 4.3 to 4.5.

Also, the performance of KEMSA was analysed and presented in Table 4.6.

4.3.1 Trends of Pull Strategy

The study intended to establish the trend in performance of each strategy adopted over

a five-year period and the following trends of pull strategy as illustrated in Table 4.3

were obtained and interpreted.

Findings in Table 4.3 indicate that outcomes of trends of pull strategy varied in each of

the years. Receiving orders outcomes were below target in 2011 and this improved in

the subsequent years. Overall mean of the outcomes was 2.2 which implied that targets

of receiving orders were achieved. This was attributed to several factors. For example,

100% of respondents indicated that the orders made were compliant with KEMSA’s

regulations and standards before processing.

- 26 -

Table 4.2: Trends of Pull Strategy

Indicators of Pull Strategy Outcome Scores

2011 2012 2013 2014 2015 Mean

Receiving orders 1 2 2 3 3 2.2

Processing orders 1 1 1 2 2 1.4

Dispatching consignments 2 2 2 2 2 2

Receiving returns 1 1 2 2 2 1.6

Processing returns 2 2 2 2 2 2

Dispatching returns consignments 2 2 2 2 2 2

Mean 1.50 1.67 1.83 2.17 2.17 1.87

Scale: N/A=0, below target=1.0-1.99, on target =2.0-2.99, exceeded target=3.0-3.99

In receiving orders, KEMSA targeted to receive orders quarterly but this varied with

some orders received after every three months (13.5 weeks). The cases of emergencies

also contributed to some orders received before period of three months was reached.

In processing the orders, the findings in Table 4.3 indicate that the exercise was not

achieving the targets, and this improved in the last two years of the assessment period.

With an overall mean of 1.4, processing orders remained a challenge as orders were

expected to be processed in a period of 48 hours if all conditions are met, yet many

orders were processed beyond the duration.

It was found that in most cases, the delay stretched to 1 week as observed by 85.7% of

KEMSA officers while in extreme situations, it took at least 14 days as observed by

14.3% of the KEMSA officers. This was attributed to several factors. The delay in

processing the orders was attributed to KEMSA’s requirement of revising some orders

especially whenever actual products as ordered were out of stock but there were

alternative products serving same purpose as observed by 85.7% of the respondents.

Also, 92.9% of respondents indicated that processing was also delayed due to some

circulars guiding new administration and usage of some medical items especially drugs.

- 27 -

On dispatching consignments, findings in Table 4.3 indicate that KEMSA has been

achieving its targets. According to KEMSA, all orders were expected to be dispatched

48 hours after processing. KEMSA therefore dispatched all consignments 48 hours after

processing. In addition, KEMSA was expected to dispatch all items agreed upon for

processing. With a mean of 2.0, there is indication that all orders processed and

dispatched 48 hours after processing were made ready for dispatch as ordered. This

outcome was confirmed by 92.9% of respondents who indicated that dispatches were

made as contained in the orders. The reconciled records in the order forms and dispatch

forms were attributed to several reasons. First, 50% of KEMSA officers indicated that

such situation was supported by availability of stock while 21.4% attributed to easy

processing of orders.

Dispatch also involved delivery of the orders. According to the findings in Table 4.3,

deliveries were made according to targets. KEMSA expected that all deliveries were to

be made within 1 week. With a mean of 2.0, KEMSA delivered as expected as observed

by 86.4% of respondents. However, some cases took between 1 and 2 weeks as

observed by 15.1% of KEMSA officers, but this was attributed to external factors such

as poor transport network occasioned by weather changes. Realising the target on

delivery was attributed to several factors that included use of outsourced logistics

services from third parties as confirmed by 71.4% of KEMSA officers. In this case,

while KEMSA employees supported some deliveries, majority of the services were

outsourced, and this increased performance as contractors in this service have

performance contracts of delivering within the expected period. This situation placed a

lot of responsibility on KEMSA of ensuring that the items reached intended destinations

within the specified period as confirmed by 84.6% of the KEMSA officers.

- 28 -

On returns, findings in Table 4.3 indicate that there was improvement in reducing

returns in the years 2013, 2014 and 2015. However, with a mean of 1.6, the targets of

receiving returns were not achieved yet KEMSA expected all consignments delivered

to match the orders. This was attributed to factors such as orders not matching deliveries

which occurred rarely. Another reason is delivery of items to the wrong facility.

With existence of returns, KEMSA was expected to process the returns and correct the

situation within a period of 48 hours. In this case, with a mean of 2.0, KEMSA realised

the target as the situation was corrected and included reconciling the order forms with

dispatch forms. In dispatch of the consignments, KEMSA consistently dispatched

correct returns. With a mean of 2.0, the target was achieved as all returns were expected

to be dispatched in less than 48 hours after processing. In this situation, priority was

given to dispatch of returns which included making deliveries in time.

Overall findings in Table 4.3 indicate that outcome scores were better (mean of 2.17)

in 2013 and 2014 while least outcomes were achieved in 2011 (mean of 1.50). The trend

is therefore a general improvement. The improvement was observed more in receiving

orders (mean of 2.2), dispatching consignments (mean of 2.0), processing returns (mean

of 2.0) and dispatching returns consignments (mean of 2.0). All these indicate achieving

or targets. However, with an overall mean of 1.87, the KEMSA did not achieve the

targets. This is attributed to challenges in processing orders (mean of 1.4) and receiving

returns (mean of 1.6). These findings indicate that outcomes of pull strategy are below

targets. These overall findings were attributed to the fact that this study covered a period

of five years which partly had a period when KEMSA adopted a new business model

and the health services had been devolved to the County Governments.

- 29 -

Table 3.4: Z-Scores for Pull Strategy

Indicators of Pull Strategy Mean z-Score

Receiving orders 2.2 .62696

Processing orders 1.4 -1.63010

Dispatching consignments 2.0 .62696

Receiving returns 1.6 -.87775

Processing returns 2.0 .62696

Dispatching returns consignments 2.0 .62696

Mean 1.87 0E-7

Standard Deviation .3011 1.0000

Findings in Table 4.4 indicate that pull strategy performed best in receiving orders,

dispatching consignments, processing returns and dispatching returns which had

positive z scores. However, this strategy had negative z scores in the processing of

orders and receiving returns. This is also attributed to KEMSA’s requirement of

revising some orders especially whenever actual products ordered were out of stock but

there were alternative products serving same purpose that the facilities could consider.

Overall findings in Table 4.4 similarly indicate that outcome scores for pull strategy

were better with a general improvement after the devolution of Health Services and

adoption of the new business model by KEMSA. These findings are also in tandem

with the recommendations by the Government’s Task Force on Performance of

KEMSA (GOK, 2008). Kamau (2006) also outlined the improved efficiency in the

distribution system by full adoption of the pull strategy especially for supply chains

with higher demand uncertainties and unit costs including low transport cost relative to

the products’ total cost.

4.3.2 Trends of Push Strategy

The following trends of push strategy as illustrated in Table 4.5 were obtained and

interpreted.

- 30 -

Findings in Table 4.5 illustrate the trends in push strategy. According to the findings,

this strategy was applied in 2011 and 2012 and not applied as from 2013. In the period

2011-2012, there was improvement in assessment of needs before processing

anticipated orders. However, with a mean of 1.0 in assessing needs of end users, the

outcome is below target. This was attributed to difficulty in making decision on items

to be supplied without consulting the end users. Thus, understanding the needs of the

end users was not clear. These findings are similar to the findings made in the previous

study (McNeil, 2007). It is clear that distribution decisions must be based on long term

forecasts with an adequate system and structure having to be in place.

Table 4.5: Trends of Push Strategy

Indicators of Push Strategy Outcome Scores Mean

2011 2012 2013 2014 2015

Assessing needs 2 3 0 0 0 1.0

Processing orders 2 2 0 0 0 0.8

Dispatching consignments 2 2 0 0 0 0.8

Receiving returns 1 1 0 0 0 0.4

Processing returns 2 2 0 0 0 0.8

Dispatching returns consignments 2 2 0 0 0 0.8

Mean 1.83 2.00 0.00 0.00 0.00 0.77

Scale: N/A=0, below target=1.0-1.99, on target =2.0-2.99, exceeded target=3.0-3.99

The findings also indicate that processing anticipated orders was on target in 2011 and

2012 after which the anticipated orders were not processed in the period between 2013

and 2015. With a mean of 0.8 in the period 2011-2015, processing orders have

outcomes that are below targets. According to KEMSA, it is expected that trends in

orders made by facilities are indicative of what should be supplied even without orders

are received. However, processing such anticipated orders were not effective due to

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several reasons that include wrong prediction and policy regulations as supported by

11.1% and 33.3% of KEMSA staff. Also, delays in processing orders was not achieved

yet KEMSA required processing of such orders to take 48 hours. For example, findings

indicate while most orders took less than one week, some took more than one week.

This was confirmed by 83.3% of KEMSA staff who stated that orders were processed

in less than week compared to 16.7% who stated that orders were processed after one

week.

In terms of dispatching orders, the outcome is below target. With a mean of 0.8 in the

period 2011-2015, dispatching orders was below target. According to KEMSA,

dispatching orders was expected to occur at least within one week, yet most orders took

one month before dispatch. This was confirmed by 76.9% of KEMSA staff who stated

that the orders were dispatched in less than week while 23.1% of KEMSA staff stated

that orders were dispatched after 1 week.

Findings on returns indicate that KEMSA received returns under this push strategy that

required processing and dispatch. With a mean of 0.4 for receiving return, this outcome

was below target as KEMSA expected no returns. The presence of returns required

processing in which mean of 0.8 indicated outcomes that were below target. According

to KEMSA, processing of returns was expected to be done within 48 hours, yet this

target was not achieved as some orders were processed after this period. This was

attributed to finding suitable match of the needs of the end user.

On dispatching the returns, findings in Table 4.5 indicate that the outcomes achieved

were below target. According to KEMSA, dispatches under push strategy are

effectively supported when deliveries are made within one week. However, with a mean

- 32 -

of 0.8, the deliveries were not done in time as some occurred beyond one week. This

was attributed to delays in transportation occasioned by logistical constraints.

Overall findings indicate that push strategy is not effective and efficient. With a mean

of 0.77, the outcomes of push strategy are below target or expectations of KEMSA.

This explains the application of the strategy in 2011 and 2012 and later not utilised in

2013-2015 period. However, having all the other conditions in place, this strategy is

still relevant to KEMSA and should not be done away with fully. This finding is

contrary to the Government’s Task Force Report (GOK, 2008).

Table 4.4: Z-scores for Push Strategy

Indicators of Push Strategy Mean z-Score

Assessing needs 1.0 1.18661

Processing orders 0.8 .16952

Dispatching consignments 0.8 .16952

Receiving returns 0.4 -1.86467

Processing returns 0.8 .16952

Dispatching returns consignments 0.8 .16952

Mean 0.77 0E-7

Standard Deviation .1966 1.0000

Findings in Table 4.6 indicate that push strategy performed best in assessing needs,

processing of orders, dispatch of consignments, processing of returns and dispatch of

return consignments over the period under study. However, this strategy had negative

z scores in the receiving of returns similar to the pull strategy. The Overall finding

indicate that despite the weakness in processing returns, push strategy still remains

relevant and can continue being applied by KEMSA. This finding is contrary to the

recommendations by the Governments Task Force of full application of pull strategy

(GOK, 2008).

- 33 -

4.3.3 Trends of Both Pull and Push Strategy

The following trends of both push and pull strategy as illustrated in Table 4.7 were

obtained and interpreted.

Table 4.7: Trends of Both Pull and Push Strategy

Indicators of Pull Strategy Outcome Scores

2011 2012 2013 2014 2015 Mean

Receiving orders 2 3 1 2 2 2.0

Processing orders 2 2 1 1 1 1.4

Dispatching consignments 2 2 1 1 1 1.4

Receiving returns 1 1 1 1 1 1.0

Processing returns 2 2 1 1 1 1.4

Dispatching returns consignments 2 2 1 1 1 1.4

Mean 1.83 2.00 1.00 1.17 1.17 1.43

Scale: N/A=0, below target=1.0-1.99, on target =2.0-2.99, exceeded target=3.0-3.99

Findings in Table 4.7 indicate that both push and pull strategies were applied and the

outcomes showed a fluctuating trend from 2011 to 2015. Receiving orders was on target

(mean of 2.0) while the rest of processes were below target (mean of 1.0-1.4). The

below target outcomes were attributed to lack of clarity on when the strategies should

be applied. Overall findings indicate that it is only 2012 that targets were achieved and

with a mean of 1.43, this strategy did not achieve its outcomes. These findings indicate

the outcomes of this strategy are below targets. KEMSA staff could also be able to

identify each of the strategies and where they could apply contrary to the findings of

(McNeil, 2007). According to Shook (2010), had also noted that a lean supply chain is

a philosophy that seeks to shorten the time between customers’ order and the shipment

of the customer by eliminating waste. But not all participants could practically or easily

apply a combination of both strategies (Shook, 2010).

- 34 -

Table 4.5: Z-Scores for both Push and Pull strategy

Indicators of both Pull and Push Strategy Mean z-Score

Receiving orders 2.0 1.76853

Processing orders 1.4 -.10403

Dispatching consignments 1.4 -.10403

Receiving returns 1.0 -1.35241

Processing returns 1.4 -.10403

Dispatching returns consignments 1.4 -.10403

Mean 1.43 0E-7

Standard Deviation .3204 1.0000

Findings in Table 4.8 similar to the finding in Table 4.7 indicate that the application of

both push and pull strategies performed best in receiving orders while the z score for

the rest of the indicators had negative values. The above outcomes were similarly

attributed to lack of clarity on when the strategies should be applied.

4.3.4 Performance of KEMSA in Supply of Medical Items

The performance of KEMSA in supply of medical items was analysed and illustrated

in Table 4.9.

Table 4.9: Performance of KEMSA

Performance Indicators Performance Scores

2011 2012 2013 2014 2015 Mean

Reduction of expiries 2 2 3 3 3 2.6

Satisfaction of end users 2 2 3 3 3 2.6

Supply of items in time 1 1 2 2 2 1.6

Deliveries matching orders 2 2 2 3 3 2.4

Stakeholder participation 1 1 2 3 3 2.0

Mean 1.6 1.6 2.4 2.8 2.8 2.24

Scale: 0.0-0.99=Very poor; 1.0-1.99= Poor; 2.0-2.99 = Fair; 3.0-3.99 = Good

The study sought to establish the trend in performance of KEMSA over the period under

study. Findings in Table 4.9 indicate that performance of KEMSA in supply of medical

items was measured based on management of expiry of drugs, satisfaction of end users,

- 35 -

just-in-time delivery of the items, making deliveries of what was ordered and

involvement of stakeholders in the supply of the items. These were similar outcomes

of the study of supply chain performance (Harrison, Lee, & Neale, 2005) The findings

also indicate that there has been improvement in performance from 2011. Much of the

improvement was observed in reducing expiries (mean of 2.6) and satisfaction of end

users (mean of 2.6). With an overall mean of 2.24, KEMSA performance is fair. This

implies that KEMSA is optimally working to ensure medical supplies are utilised by

the end users which are similar indicators from the study that indicated that in such

systems they should be responsive to market changes, inventories and obsolescence

(Wang' & Wittwer, 2007)

Table 4.6: Z-Scores for KEMSA Performance

Performance Indicators Mean z-Score

Reduction of expiries 2.6 .83028

Satisfaction of end users 2.6 .83028

Supply of items in time 1.6 -1.47605

Deliveries matching orders 2.4 .36901

Stakeholder participation 2.0 -.55352

Mean 2.24 0E-7

Standard Deviation .4335 1.0000

Findings in Table 4.10 indicate that performance of KEMSA in supply of medical items

was critically pegged on reduction of expiry, satisfaction of end users, and deliveries

matching orders all of which had positive z scores. The findings also indicate that just

in time supply and stakeholder participation are not major determinants of performance

as they had a negative z score.

4.4 Impact of the Distribution Strategies on the Performance of KEMSA

Impact of each of the distribution strategies on performance of KEMSA in supply of

medical items was determined and described in Tables 4.7 and 4.8:

- 36 -

4.4.1 Correlations

Correlations between variables were obtained and illustrated in Table 4.7.

Table 4.7: Correlations between Variables

Strategy Performance

Both

Pearson Correlation .789

Sig. (2-tailed) .720

N 6

Pull

Pearson Correlation .389

Sig. (2-tailed) .446

N 6

Push

Pearson Correlation .053

Sig. (2-tailed) .920

N 6

Correlation is significant at the 0.05 level (2-tailed).

Findings in Table 4.7 indicate that there is strong correlation (r=0.789) between both

(pull and push strategy) and performance. The findings, however, indicate weak

correlation between pull strategy and performance (r=.389) as well as push strategy and

performance (r=.053). These findings imply that performance of KEMSA is significant

when the two strategies (push and pull) are applied together. Wang’ & Wittwer (2007),

also noted that the combination of the two strategies have a significance of

performance. The high demand of the uncertainty encourages high pull strategy level

while the high scale of economy provides incentive to the great degree of the push

system.

4.4.2 Model Summary

A determination on how each strategy affects performance was done through

development of regression model. The findings are illustrated in Table 4.8.

Table 4.8: Model Summary

Model R R

Square

Adjusted

R Square

Std. Error of

the Estimate

0.866a .751 .377 .50332

- 37 -

a. Predictors: (Constant), Both, Push, Pull

Table 4.8 shows the coefficient of determination R2 which tells us how variation in

factors (push strategy, pull strategy, both push and pull strategy) explains the changes

or variation in performance of KEMSA. With R2 .866 for the model, this means that

the independent variables (predictors) in the model (push strategy, pull strategy, both

push and pull strategy) could offer about 86.6% explanation of the variation in the

dependent variable (KEMSA performance in supply of medical items).

This means that as the factors change, KEMSA performance varies by 86.6%. This is a

high relationship since 13.4% remaining is explained by other variables or factors not

included in the model and represented by the error term. Hence the results reveal that

the independent variables (factors) are key determinants of performance KEMSA.

4.4.3 Distribution of Coefficients

A determination on how each strategy affects performance was done through regression

analysis. The findings are illustrated in Table 4.9.

Table 4.9: Regression Results

Coefficients a Unstandardized

coefficients

Standardized

coefficients

B Std. Error Beta t Sig.

(Constant b) 3.150 1.424 2.213 .157

Pull 1.778 .969 .839 1.835 .208

Push 1.139 2.761 1.276 1.499 .273

Both 3.750 1.780 1.884 2.107 .170

a. Dependent Variable: Performance

Table 4.9 shows that there was a positive relationship between all variables and

KEMSA performance: Pull strategy (β = 1.778, t = 1.835); Push strategy (β =1.139, t

=1.499); both push and pull strategy (β = 3.750, t =2.107). Furthermore, the

- 38 -

significance levels were analysed and as shown in the table, all the variables had a

significant relationship with KEMSA performance at p<0.05).

Overall findings indicate that the consistency of regression coefficients on the

predictors in the model suggest that these variables are important factors influencing

KEMSA performance but at varying degrees. From the regression model the following

regression equation is derived:

Y = 3.150+ 1.778X1+ 1.139X2+3.750X3+.134X4+ε

Where:

Y = KEMSA performance

X1= Pull strategy

X2= Push strategy

X3= Both pull and push strategy

X4= Other unmeasured factors

ε = Error Term

Constant = 3.150, shows that if the factors are rated as zero, KEMSA performance

would change by a factor of 3.15. The independent variables have varying degree of

impact on KEMSA performance depending on beta coefficients values.

The performance of KEMSA is affected at different degrees by the distribution strategy

adopted. In other words, these strategies are important factors influencing KEMSA

performance but at varying degrees. The results also show that both push and pull

strategy improves KEMSA performance more than the pull strategy and push strategy

alone.

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CHAPTER FIVE: SUMMARY, CONCLUSION AND

RECOMMENDATIONS

5.1 Introduction

This chapter highlights major findings obtained from the analysis on all the data

collected. The chapter also presents relevant conclusions and recommendations.

5.2 Summary of Findings

This study was conducted with the aim of finding whether KEMSA employed best-in-

class SCM practices. The first objective was to identify the medical distribution

strategies adopted by KEMSA. The second objective was to determine the impact of

the distribution strategies adopted on the performance of KEMSA.

On distribution strategy adopted by KEMSA, the study established that KEMSA

adopted three strategies. It adopted pull strategy, push strategy and mixed strategy

comprising of both push and pull elements. Pull strategy was most preferred while

application of push strategy reduced in the period between 2011 and 2015. The

increasing application of pull strategy from 2011 is attributed to effects of devolution

where health sector was mainly managed by County Governments that took control

over procurement of medical supplies.

The study also established general improvement in application of pull strategy. The

improvement was observed more in receiving orders, dispatching consignments,

processing returns and dispatching returns consignments All these indicated

achievement of targets. However, with an overall mean of 1.87, the KEMSA did not

achieve the targets. This was attributed to challenges in processing orders and receiving

returns. These findings indicated that outcomes of pull strategy were below targets.

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On push strategy, the study established that push strategy was applied in 2011 and 2012

and not applied thereafter. With a mean of 0.77, the outcomes of push strategy were

below target or expectations of KEMSA. It was expected that assessment of needs,

processing orders, dispatching orders, receiving returns, processing returns and

dispatching returns to be above targets. However, the not all the processes were on

target.

On mixed strategy comprising of some push and pull elements, the study established

that there was fluctuation in the trends between 2011 and 2015. Overall findings

indicated that it is only in 2012 that targets were achieved and with a mean of 1.43, this

strategy did not achieve its outcomes.

On performance of KEMSA, the study established that there was improvement in

performance of the institution from 2011. Improvement was observed in management

of expiry of drugs, satisfaction of end users, just-in-time delivery of the items, making

deliveries of what was ordered and involvement of stakeholders in the supply of the

items. This implied that KEMSA was optimally working to ensure medical supplies are

utilised by the end users.

The findings on impact of the distribution strategy adopted on performance of KEMSA

revealed that there was strong correlation between both pull and push strategies and

performance. The findings, however, indicated weak correlation between pull strategy

and performance as well as a weak correlation between push strategy and performance.

The study also established that the strategies adopted explained about 86.6% in

performance of KEMSA in distribution of medical items.

The study also established that all strategies employed are important factors influencing

KEMSA performance but at varying degrees. In the regression model derived, mixed

strategy contributed most to the performance followed by pull strategy and then push.

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From the model, other factors not measured in this study only contributed 13.4% of the

performance of KEMSA.

5.3 Conclusions

In the view of all this mission of the study, this study concludes that while KEMSA has

adopted three supply chain strategies, the pull strategy is most applied due to

governance changes where County Government hospitals are making major decision

on when the medical items are to be supplied. The study also concludes that while pull

strategy is most applied, the performance of KEMSA is largely affected by application

of combination of both push and pull strategies. However, while the performance of

KEMSA is largely determined by combination of both push and pull strategies, it

remains fair and there is opportunity for improvement in the supply chain.

5.4 Recommendations

This study recommends KEMSA to continue applying push strategy as it remains

relevant to its internal performance. KEMSA should address challenges in the strategies

especially on supplying items on time. This can be improved if KEMSA has a clear

communication between order processing and distribution schedule. KEMSA should

maintain proper data as this plays a key role in the continued application of push

strategy. This strategy requires historical data to determine the supplies that are required

by various regions at different periods.

5.5 Limitations of the Study

This did not exhaust all the factors that influence distribution performance at KEMSA.

In addition, the study focused on the performance trend over a period of five years and

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therefore did not capture the trend in performance after adoption of new business

model.

5.6 Suggestions for further Studies

There is a need for further research to identify any other factor that impacts distribution

of pharmaceuticals and medical equipment. Such factors may relate to geographical

challenges, poor infrastructure, politics, and even legal mandate of KEMSA. Further

research needs also to be carried out on performance of other institutions’ that distribute

medical drugs and equipment as well as the trend in performance after devolution of

Health services.

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APPENDICES

Appendix 1- Introduction Letter

- 49 -

Appendix 2- Questionnaire

QUESTIONNAIRE TO KEMSA EMPLOYEES ON THE

DISTRIBUTIONSTRATEGIES AND PERFORMANCE OF KEMSA

This study is meant to capture the distribution strategies at the Kenya Medical Supplies

Authority and the subsequent impacts on its performance as part of its core mandate of

the distribution of essential drugs and medical equipment in Nairobi County.

Kindly provide the most accurate information regarding each of the items in the

questionnaire as it is at KEMSA. The study will take approximately 15 minutes of your

time. Please remember this study is for academic purposes only and your information

will be kept as confidential. There is no right and wrong answer.

PART I

What distribution strategy is adopted by KEMSA in the distribution of medical drugs

and equipment in Nairobi area?

Push strategy [ ] Pull strategy [ ] Both push & pull [ ]

If pull, do you make the actual deliveries as contained in the orders?

Yes [ ] No [ ]

If Yes, what reasons would attribute this to?

Availability of stock [ ]

Availability of staff [ ]

Easy processing of the orders [ ]

Clear and easy approval process [ ]

If No, what are the reasons for the variation?

Stock out [ ]

Expiries [ ]

Failure to submit appropriate orders and/or documents as required [ ]

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Lack of internal approval [ ]

Donor requirements [ ]

Do most orders made meet KEMSA’s regulations and standards before processing?

Yes [ ] No [ ]

If Yes, how long do you take to process such orders?

Less than 1 week [ ] 1-2 weeks [ ] 2-4 weeks [ ] Above 4 weeks [ ]

If No, what do you do?

Refer orders back to facilities [ ]

Reject the orders [ ]

Seek clarification where necessary [ ]

Do you mostly dispatch the actual quantities as ordered?

Yes [ ] No [ ]

If Yes, give reasons

Stock availability [ ]

Staff availability [ ]

Status consideration e.g emergency response [ ]

Policy change [ ]

If No, give reasons:

Stock outs [ ]

Lack of staff [ ]

Policy change [ ]

Approval process [ ]

How long does it take to deliver the items ordered to the facilities after processing and

approval?

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Less than 1 week [ ] 1-2 weeks [ ] 2-4 weeks [ ] Above 4

weeks [ ]

Who makes the deliveries?

KEMSA staff [ ] Outsourced/third party [ ] Health facility [ ]

In cases of delay in making deliveries, who takes up the responsibility?

KEMSA staff [ ] Outsourced/third party [ ] Health facility [ ]

Do deliveries meet the expectations of the facilities (are in line with orders made)?

Yes [ ] No [ ]

If Yes, give reasons:

Correct description of the orders [ ] Easy processing of the orders [ ] If

No, give reasons:

Inability to understand the orders [ ]

Inability to process the orders [ ]

Stock outs [ ]

If push strategy is used, do you meet the actual requirements of the facilities?

Yes [ ] No [ ]

If Yes, what reasons would attribute this to?

Availability of stock [ ]

Availability of staff [ ]

Understanding of facilities’ needs [ ]

If No, what are the reasons for the variation?

Stock out [ ]

Expiries [ ]

Lack of internal approval [ ]

How long does it take to deliver the items to the facilities after dispatch?

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Less than 1 week [ ] 1-2 weeks [ ] 2-4 weeks [ ]

Above 4 weeks [ ]

If push strategy is involved, do you deliver items that are required by the facilities?

Yes [ ] No [ ]

If push strategy is involved, what guides the identification of items to be processed and

delivered?

Prediction [ ] Guessing [ ] Frequency of orders made [ ]

Policy [ ] Outbreak of diseases [ ] Increased demand [ ]

Others [ ] (please specify) ………………………………………………..

If push strategy is applied, what is the average time taken to process the deliveries?

Less than 1 week [ ] 1-2 weeks [ ] 2-4 weeks [ ]

Above 4 weeks [ ]

If push strategy is involved, how long does it take to deliver the items to the facilities

after dispatch?

Less than 1 week [ ] 1-2 weeks [ ] 2-4 weeks [ ]

Above 4 weeks [ ]

What is the frequency of applying push strategy in every three months?

Few times [ ] Many times [ ]

If both push and pull strategies are applied, which strategy do you prefer?

Push strategy [ ] Pull strategy [ ]

Give reasons:

Easy to administer [ ] Encourages stakeholder participation [ ]

Others [ ] (please specify) ………………………………………………..

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In your own opinion, what are your recommendations to improvement of the

distribution system at KEMSA?

………….………….………….………….………….…………………………………

…………………………………………………………………………………………

………………………………………………………………….

THANKS

PART II

Distribution summary form

Variables -If pull strategy used 2012 2013 2014 2015 2016

Time of receiving orders (if any)

Time expected to process orders

Actual Time of processing orders

Expected time after processing to

dispatch consignment

Actual Time of dispatching

consignment

Quantity of orders made

Quantity processed and dispatched

Frequency of orders made

Frequency of orders processed and

consignment dispatched

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PART II

Distribution summary form

Variables -If push strategy used 2012 2013 2014 2015 2016

Time of dispatching orders

Time expected to process orders

Expected time after processing to

dispatch consignment

Actual Time of dispatching

consignment

Quantity of orders dispatched

Frequency of dispatching orders